Hindawi Publishing Corporation
Advances in Environmental Chemistry
Volume 2014, Article ID 958134, 8 pages
http://dx.doi.org/10.1155/2014/958134
Research Article
Experimental Design of Photo-Fenton Reactions for
the Treatment of Car Wash Wastewater Effluents by
Response Surface Methodological Analysis
Maha A. Tony1,2 and Zeinab Bedri3
1
Green Chemistry Centre of Excellence, Department of Chemistry, University of York, York YO10 5DD, UK
Basic Engineering Science Department, Faculty of Engineering, Minoufiya University, Shebin El Koum, Minoufiya 32511, Egypt
3
Centre for Water Resources Research, School of Architecture, Landscape and Civil Engineering, University College Dublin,
Newstead, Belfield, Dublin 4, Ireland
2
Correspondence should be addressed to Maha A. Tony; maha tony1@yahoo.com
Received 2 May 2014; Revised 20 July 2014; Accepted 4 August 2014; Published 25 August 2014
Academic Editor: Huu Hao Ngo
Copyright © 2014 M. A. Tony and Z. Bedri. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly
cited.
Establishing a treatment process for practical and economic disposal of car wash wastewater has become an urgent environmental
concern. Photo-Fenton’s process as one of the advanced oxidation processes is a potentially useful oxidation process in treating
such wastewater. Lab-scale experiments with UV source, coupled with Fenton’s reagent, showed that hydrocarbon oil is degradable
through such a process. The feasibility of photo-Fenton’s process to treat wastewater from a car wash is investigated in the present
study. A factorial design based on the response surface methodology was applied to optimize the photo-Fenton oxidation process
conditions using chemical oxygen demand (COD) reduction as the target parameter to optimize. The reagent (Fe2+ and H2 O2
concentration) and pH are used as the controlling factors to be optimized. Maximal COD reduction (91.7%) was achieved when
wastewater samples were treated at pH 3.5 in the presence of hydrogen peroxide and iron in amounts of 403.9 and 48.4 mg/L,
respectively.
1. Introduction
Car washing leads to disposal of large amounts of oily polluted water which results in potentially high levels of nutrients, metals, and hydrocarbons flowing into storm drains.
The composition of pollutants found in car wash wastewater
varies according to the way of washing, mechanical car
washing or artificial high-pressure water washing, and the
size and type of vehicle (e.g., small car, truck, commercial van,
etc.). In some cases, car wash wastewater may also contain
heavy metals [1–3].
Considering the large volume of wastewater generated
from the car washing process, wastewater treatment coupled
with recycling may possibly be an essential water quality
measure. For instance, in the US, commercial car wash
facilities either recycle or treat their wash water prior to
discharge to the sanitary sewer system, so most storm water
impacts from car washing are from residential car wash
systems that discharge polluted wash water into the storm
drain system [1]. Some countries, for example, Switzerland,
Germany, and The Netherlands, no longer allow outdoor car
washing away from car washing stations [4].
In Egypt, as well as in many countries worldwide, car
wash activities within petrol stations and outdoor car washing
are among those activities that pose an environmental threat
to the main freshwater source, the river Nile, which is already
subjected to untreated wastewater [5]. Consequently, there is
a growing need for research particularly on the application
of innovative technologies in the treatment of such kind of
wastewater.
The development of novel treatment methods encompasses investigations of advanced oxidation processes
(AOPs), which are characterized by the production of the
hydroxyl radical (∙ OH) as a primary oxidant [6]. Examples of
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Advances in Environmental Chemistry
Table 1: Properties of chemicals used in the study1 .
Compound
Iron chloride tetrahydrate
Hydrogen peroxide
Sulfuric acid
1
Molecular weight
198.8
134.01
98.08
Formula
FeCl2 ⋅4H2 O
H2 O2
H2 SO4
Manufacturer
Sigma-Aldrich
Sigma-Aldrich
Sigma-Aldrich
Purity
98.0%
30 wt%
97.0%
Hydrogen peroxide solution with a stabilizer (dipicolinic acid (approximately 40 mg/L)).
AOPs include the use of hydrogen peroxide with ultraviolet
light (H2 O2 /UV) to treat hazardous compounds [7],
Fenton and photo-Fenton reagent (H2 O2 /Fe2+ ) [8–10],
semiconductor photocatalysis [11], and the sonolysis process
using ultrasonic irradiation [12]. Among various AOPs, the
Fenton reagent is one of the most effective methods for
treating various industrial effluents including wastewater
[13, 14] and oily wastewater [15]. Previous work by the
authors has involved the application of Fenton and the
photo-Fenton reagents for the treatment of water polluted
with diesel oil emulsion [10, 16]. Although Fenton reagent
has been reported extensively in the literature, there is a
scarcity of publications focusing on its use for the treatment
of car wash wastewater.
The main aim of the present study is to explore the
possibility of treating car washing water to an acceptable level
that can be recycled and reused for the same application.
The study is of both national and international importance
as it targets two global water issues: water conservation
and water pollution. The study outlines the application of
the photo-Fenton process to the mineralization of car wash
wastewater. The effect of the reaction operating conditions
is investigated and the factors that control the Fenton reaction process (Fe2+ , H2 O2 , and pH) are optimized. Furthermore, the experimental design of the study applies a wellestablished [17–19] statistical-based technique, commonly
known as RSM (response surface methodology) [20], to
explore optimum range of values of Fe2+ , H2 O2 , and pH for
the maximum COD removal.
Factors to control the Fenton reaction process are the
amounts of Fe2+ and H2 O2 and the working pH. Optimizing
such parameters plays a key role towards the achievement
of the Fenton reaction. The experimental design using
a statistical-based technique, commonly known as RSM
(response surface methodology) [20], has been increasingly
applied in many fields including wastewater treatment to
study the optimization of the treatment process.
2. Materials and Methods
2.1. Car Wash Wastewater. Wastewater samples were collected from a car washing wastewater tank at a petrol
station in the south of Egypt. The principal properties of the
wastewater are 82 mg-COD/L, turbidity of 28.1 NTU, pH 8.2,
and suspended solids of 55 mg/L.
2.2. Experimental Materials. Fe2+ in Fenton’s reagent
(Fe2+ /H2 O2 ) is prepared by making a solution from Fe2+
salt. H2 O2 was obtained in liquid (30% of H2 O2 , wt) from
UV lamp
Fe2+
H2 O2
Samples after
treatment
Raw car wash
wastewater
Magnetic stirrer
Fenton’s reagent operating
parameters optimization
using RSM
COD instrument for
analysis
Figure 1: Schematic diagram of a lab-scale photo-Fenton test.
a commercial supplier. Sulfuric acid is used for adjusting the
pH of the wastewater samples during treatment. Properties
of chemicals used in this study are listed in Table 1.
2.3. Methodology. All photochemical experiments were carried out in a batch mode laboratory scale unit using a
250 mL beaker. Initially, the pH value of 100 mL of the car
wash wastewater samples was adjusted at the desired values
with sulfuric acid before being subjected to oxidation. Then,
ferrous ions solution and hydrogen peroxide were added to
produce hydroxyl radicals. Subsequently, the mixture was
subjected to magnetic stirring and UV radiation (254 nm
wavelength), as illustrated in Figure 1. Samples were taken at
regular time intervals in the discontinuous experiments and
analyzed.
2.4. Analytical Determinations. The COD measurements
were performed using HACH analyser (model HACH
DR-2400). Turbidity was undertaken using a HACH 2100N
IS Turbidity meter (ISO method 7027). The pH of the
wastewater was adjusted using a digital pH-meter (model
PHM62 Radiometer).
2.5. Experimental Design. The Fenton oxidation process was
optimized by applying the response surface methodology
[20]. COD removal, defined by (1), of the effluents was used
as the variable to be optimized. The amounts of H2 O2 , Fe2+ ,
and pH were chosen as the control factors to be optimized.
Advances in Environmental Chemistry
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Table 2: Range and levels of natural and corresponding coded variables for RSM.
Symbols
Variable
Natural
𝛿1
𝛿2
𝛿3
2+
Fe (mg/L)
H2 O2 (mg/L)
pH
Range and levels
0
40
400
6
−1
30
350
3.5
Coded
𝑥1
𝑥2
𝑥3
1
50
450
8.5
Table 3: RSM for the three experimental variables in coded units and corresponding natural values.
Experiment number
Fe2+ (mg/L)
30
30
50
50
40
40
40
40
30
50
30
50
40
40
40
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Natural variable
H2 O2 (mg/L)
350
450
350
450
350
350
450
450
400
400
400
400
400
400
400
The initial design involved 15 tests, based on a three-level BoxBehnken factorial design [20]:
𝜂 (%) =
COD𝑜 − COD
× 100,
COD𝑜
3
3
𝑖=1
𝑖=1
𝑖 𝑗=𝑖+1
(2)
where 𝜂 is the predicted response; 𝑖 = 1, 2, 3 and 𝑗 =
1, 2, 3; 𝛽𝑜 is the constant coefficient (intercept); 𝛽𝑖 are the
linear coefficients; 𝛽𝑖𝑗 are the cross product coefficients; and
𝑋𝑖 is the input controlling coded variable. In addition, the
natural variables of the operating system (𝜉𝑖 ) were transferred
to coded variables (𝑋𝑖 ) according to (3) [20] to simplify
the model calculations. The results of COD removal and
the turbidity were analysed through the statistical analysis
𝑥1
−1
−1
1
1
0
0
0
0
−1
1
−1
1
0
0
0
Coded variable
𝑥2
−1
1
−1
1
−1
−1
1
1
0
0
0
0
0
0
0
𝑥3
0
0
0
0
−1
1
−1
1
−1
−1
1
1
0
0
0
software package of SAS Institute, Inc., [17] by performing
the analysis of variance (ANOVA) and fitted with a secondorder polynomial model:
(1)
where 𝜂 is the percentage of COD removal; COD𝑜 measured
COD in supernatant before oxidation (mg-O2 /L); and COD
is the COD value after the treatment.
The first step in the RSM is to find a suitable approximation for the true functional relationship between the response
(𝜂) and the set of independent variables. The following
response function was used to correlate the dependent and
independent variables in the response surface:
𝜂 = 𝛽𝑜 + ∑𝛽𝑖 𝑋𝑖 + ∑𝛽𝑖𝑖 𝑋𝑖2 + ∑ ∑ 𝛽𝑖𝑗 𝑋𝑖 𝑋𝑗 ,
pH
6
6
6
6
3.5
8.5
3.5
8.5
3.5
3.5
8.5
8.5
6
6
6
𝑥𝑖 =
(𝛿𝑖 ) − (its upper level + its lower level) /2
.
(its upper level − its lower level) /2
(3)
The combined effect of the three independent variables,
that is, Fe+2 concentration, H2 O2 concentration, and initial
pH, is represented as 𝛿1 , 𝛿2 , and 𝛿3 , respectively. The range of
the experimental variables investigated in the study and the
time of reaction (1 hr) were chosen according to preliminary
tests. Therefore, each variable ranged between −1 and 1, as
the lower and upper levels, respectively. These ranges and
levels are presented in Table 2. Fifteen runs were required for
a complete set of the experimental designs.
3. Results and Discussions
3.1. Model Fitting. The three-level experiments were carried
out according to the Box-Behnken design and the experimental plan is shown in Table 3 as coded and natural levels.
The data shows the results of the photo-Fenton experiments
as an average of three duplicate experimental results at each
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Table 4: Experimental and predicted achieved removal responses
for RSM.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
𝜂 (%)
Experimental results Predicted response
68
72
88
84
93
96
90
86
98
90
71
71
88
88
68
76
84
88
98
102
78
74
89
85
29
29
31
29
28
29
operating condition. The following is the second-order fitting
polynomial equation of coded factors:
𝜂 (%) = 29.30 + 6.48𝑋1 + 0.60𝑋2 − 7.70𝑋3 + 30.86𝑋12
− 5.50𝑋1 𝑋2 − 0.75𝑋1 𝑋3 + 24.63𝑋22 + 1.85𝑋2 𝑋3
+ 27.18𝑋32 .
(4)
The values of COD of the car washes wastewater as the
responses obtained from the experiments and the predicted
values are shown in Table 4 and plotted in Figure 2. A satisfactory agreement between the experimental and predicted
data is achieved (Table 4). This is confirmed in Figure 2 which
shows a regression coefficient 𝑅2 value of 0.97 (the model
being rejected if the 𝑅2 value is less than 0.8 [20]). Thus, it is
reasonable to state that the polynomial model (2) is a reliable
tool to describe the Fenton reaction behaviour in car washing
wastewater treatment.
3.2. Statistical Analysis. The effect of a certain factor is the
change in response produced by the change in the level of
that factor. When the effect of a factor depends on the level
of another factor, the two factors are said to be interacting.
In order to further assess the polynomial model (4) taking
into account the interaction of factors, statistical analysis of
variance (ANOVA) using SAS software was conducted and
the statistical significance of the factors towards the response
(𝜂) of the process was determined by Fisher’s 𝐹-test (𝐹-value
is the ratio of mean square of regression to the mean square of
the error) [17, 20]. Student’s 𝑡-test was used to determine the
significance of the regression coefficients of the parameters.
The probability values (𝑃 values) were used as a tool to check
the significance of the model. In general, if the significance
probability value (𝑃 > 𝐹) is small (below 0.05) and the
100
Predicted COD removal (%)
Experiment number
120
80
60
40
20
0
0
20
60
40
80
Experimental COD removal (%)
100
120
Figure 2: Predicted versus experimental data for COD removal (%)
(𝑅2 = 0.97).
𝑃 value is lower than 0.01, the model is acceptable [17].
ANOVA of the tested model (Tables 5 and 6) indicated that
the model is significant since the 𝐹-model is 19.94 and has a
low probability value (𝑃 > 𝐹 = 0.002105).
The response (COD removal, %) surfaces of
two-dimensional contour plots and three-dimensional
curves, generated by MATLAB 7.0, notably illustrate the
relations between two interacting factors with the response
(𝜂), while the third factor was kept constant at zero. Figure 3
shows the response under the variable concentrations of
Fe2+ and H2 O2 . It demonstrates a considerable enhancement
of COD removal (%) when the H2 O2 concentration was
increased. However, at higher concentrations of H2 O2 the
reduction rate was negatively affected. This trend (the decline
of % COD removal with H2 O2 concentrations higher than
the optimum) is more evident when the iron concentration
is low. Thus, an increase in the concentration of this reagent
does not grant a continuing improvement to the COD
removal efficiency of the treated wastewater. Similarly, the
reduction percentage of COD demonstrated an increase with
increasing Fe2+ concentration to a certain point after which
it became slower. This indicates that there is an optimal
dosage for both Fe2+ and H2 O2 concentrations. Similarly, the
3D surface and the corresponding contour plot in Figure 4
show that the combination of Fe2+ concentration and pH
has a significant effect on COD removal. The detrimental
effect of higher H2 O2 concentration is probably due to both
autodecomposition of H2 O2 into oxygen and water and the
recombination of OH radicals [21]. If either H2 O2 or Fe2+ is
not present in optimal dosage, it will scavenge OH radicals
and reduce their available amount in solution [19]. Figure 5
demonstrates that the increase in pH with the increase in
the H2 O2 concentration enhanced the rate of COD removal
in a certain zone, beyond which less reduction of COD is
observed. Therefore, optimising the sensitive parameters
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1
0.8
0.6
100
0.4
0.2
60
0
x2
COD (%)
80
−0.2
40
−0.4
20
1
−0.6
0.5
1
x2
−0.8
0.5
0
0
−0.5
−1
−1
x1
−0.5
−1 −1
−0.8 −0.6 −0.4 −0.2
0
x1
0.2
0.4
0.6
0.8
1
(b)
(a)
Figure 3: 3D surface and contour plot of response surface curve for COD removal showing interaction between (a) Fe2+ and (b) H2 O2 .
1
0.8
0.6
COD (%)
0.4
0.2
100
0
x3
120
80
−0.2
60
−0.4
40
−0.6
20
1
0.5
x3
0
−0.5
−0.5
−1
−1
0.5
0
1
−0.8
−1
−1
x1
−0.8 −0.6 −0.4 −0.2
0
x1
0.2
0.4
0.6
0.8
1
(b)
(a)
Figure 4: 3D surface and contour plot of response surface curve for COD removal showing interaction between Fe2+ and pH.
Table 5: ANOVA coefficient of regression and 𝑡 checking1 .
Variable
𝑋1
𝑋2
𝑋3
𝑋1 𝑋1
𝑋1 𝑋2
𝑋1 𝑋3
𝑋2 𝑋2
𝑋2 𝑋3
𝑋3 𝑋3
1 2
Standard deviation
2.405956
2.405956
2.405956
3.541472
3.402536
3.402536
3.541472
3.402536
3.541472
𝑇
2.691238
0.249381
−3.20039
8.704009
−1.61644
−0.22042
6.953324
0.543712
7.673364
𝑅 : coefficient of determination; values were 0.97 for COD percent removal.
𝑃>𝑡
0.043235
0.812987
0.023985
0.000331
0.166922
0.834259
0.000945
0.609995
0.000599
Coefficient
6.475
0.6
−7.7
30.825
−5.5
−0.75
24.625
1.85
27.175
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Table 6: Analysis of variance (ANOVA) for the RSM model.
Source
Model
Linear
Square
Interaction
Error
Total
Degree of freedom (df)
9
3
3
3
5
14
Sum of squares (SS)
8309.248
812.605
3631.609
4979.369
231.545
8540.793
Mean squares (MS)
923.2498
812.605
3631.609
4979.369
46.309
𝐹 statistics
19.93673
17.547452
78.42124
107.52485
𝑃>𝐹
0.002105
0.880207
1.001512
0.611539
Table 7: Optimum values of the process parameters for maximum
efficiency.
100
Parameter
𝜂 (COD reduction rate, %)
Fe2+ (mg/L)
H2 O2 (mg/L)
pH
COD (%)
80
60
40
20
1
0.5
x3
0
0.5
0
−0.5
−0.5
1
x2
−1 −1
(a)
1
0.8
0.6
0.4
x3
0.2
0
−0.2
−0.4
−0.6
−0.8
−1
−1
−0.8 −0.6 −0.4 −0.2
0
x2
0.2
0.4
0.6
0.8
1
(b)
Figure 5: 3D surface and contour plot of response surface curve for
COD removal showing interaction between H2 O2 and pH.
(Fe2+ , H2 O2 concentrations, and pH) was conducted to
achieve the highest COD removal for the system.
3.3. Optimization Analysis. Using the method of experimental factorial design and response surface analysis, the optimal
conditions for COD removal percentage by photo-Fenton’s
reagent can be determined. Optimum values of the selected
Optimum value
91.7
48.4
403.9
3.5
variables can be achieved by solving the regression equation
(using MATHEMATICA software (V 5.2)). The optimum
values of the test variables in-coded were as follows: Fe+2
dosage, 𝑥1 = 48.4 mg/L, H2 O2 dosage, 𝑥2 = 403.9 mg/L,
and pH, 𝑥3 = 3.5, while the predicted response was 91.7%.
According to the relation between 𝛿𝑖 and 𝑥𝑖 , the natural values
of the test variables are shown in Table 7. This finding is in
agreement with the previous observation of Tony et al. [16]
and Kositzi et al. [22] for the treatment of wastewater.
The optimal molar ratio H2 O2 : Fe+2 in the present study
is 12 : 1; hence, the hydrogen peroxide is in excess. This
optimal molar ratio compares well with the molar ratio of
11 : 1 given by Tang and Huang [23] for 2,4-dichlorophenol
degradation.
Increasing H2 O2 concentration results in the generation
of additional reaction intermediates (∙ OH) radicals which
enhances the degradation process. However, at higher peroxide concentrations, the excess hydrogen peroxide can act as
an ∙ OH scavenger, forming HO∙ 2 , which is also a free radical
produced in situ from the H2 O2 but is a less reactive oxidizing
agent and therefore has a longer life time than the ∙ OH and
the result is a reduction in the overall reaction rate [24, 25].
Moreover, iron concentrations above the optimal value result
in reduced process performance because more species of iron
ions are produced rather than the more useful ∙ OH radicals.
This finding is in agreement with the previous observation of
Kositzi et al. [22].
The recommended pH value in this investigation of pH
3.5 is well in agreement with the suggested value of 3.0
by Fongsatitkul et al. [26] in the treatment of wastewater
from textile industry. These findings clearly suggest that the
optimal ratio of the reagent concentration and the pH value
vary in accordance with the type of the substance to be
treated.
3.4. Verification of the Results. In order to validate the
efficiency of the model, three additional experiments using
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Table 8: Predicted and experimental values for the responses at
optimum conditions.
Type of value
Predicted
Experimental
COD reduction, %
91.7
93.4
these optimum operating conditions were conducted. The
duplicate experiments yielded an average COD removal
percentage of 97%. The predicted COD reduction efficiencies
(%) via (2) are jointly shown in Table 8. A good agreement of
the data between the experimental and the predicted can be
obtained with regression coefficient 𝑅2 value of 0.97 (plotting
is shown in Table 2). Thus, it is reasonable to believe that
the polynomial model (2) is a reliable model to describe the
Fenton reaction behaviour in the wastewater treatment.
4. Conclusion
Results from the present study have demonstrated the
effectiveness of the application of photo-Fenton reagent
(Fe2+ /H2 O2 ) in the treatment of wastewater delivered from
car wash centres. The response surface methodology for
optimising such process parameters was applied. This experimental design methodology was shown to be a valuable
tool in optimizing the process, which could be satisfied with
the minimum number of experiments. The three statistical
variables, Fe2+ , H2 O2 concentrations, and pH, showed optimal values, giving maximum percentage COD reduction that
reached 97% in treating such car washing water used in the
study. The optimal molar ratio of H2 O2 : Fe2+ was found to
be 12 : 1 and the optimum pH was 3.5. These findings are
comparable to the literature. This demonstrates the usefulness
and effectiveness of the Fenton reagent as an advanced
technique for the treatment process.
Conflict of Interests
The authors declare that there is no conflict of interests
regarding the publication of this paper.
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